{"id":"W1650907380","doi":"10.1109/taes.2015.140507","title":"Digital VLSI architectures for beam-enhanced RF aperture arrays","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Aerospace and Electronic Systems","topic":"Antenna Design and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Beamforming; Gate array; Infinite impulse response; Computer science; Electronic engineering; Phased array; Aperture (computer memory); Digital filter; Engineering; Computer hardware; Field-programmable gate array; Bandwidth (computing); Telecommunications; Physics; Acoustics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007437646,0.0001963143,0.0002006696,0.00007683282,0.00009656339,0.0001096086,0.00007073866,0.0001213921,0.000002722045],"category_scores_gemma":[0.000005179616,0.0001763974,0.0000672953,0.0001245467,0.00002630078,0.00006835236,3.156998e-7,0.0001972359,0.00001422724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001144996,"about_ca_system_score_gemma":0.00005466701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008365543,"about_ca_topic_score_gemma":0.00003513044,"domain_scores_codex":[0.9991338,0.000009548376,0.0001510705,0.0001973097,0.0001263027,0.000381929],"domain_scores_gemma":[0.9995899,0.00006864099,0.00002419027,0.0001461053,0.00004715023,0.0001239634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001162477,0.00003894372,0.000004692588,0.00009350736,0.0001183714,6.048709e-7,0.0005041634,0.9751351,0.01712307,0.00006526531,0.001085331,0.005714741],"study_design_scores_gemma":[0.003571345,0.001359131,0.000009850149,0.0002060255,0.0001223559,0.0001016116,0.001569153,0.9297543,0.04116306,0.0001788708,0.02087533,0.001088923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02380314,0.001240113,0.9729357,0.00006825203,0.0004181624,0.0004520254,0.00003397589,0.0002695758,0.0007790608],"genre_scores_gemma":[0.9970108,0.0001246764,0.0001258978,0.00004036872,0.00009376255,0.0001169428,0.000008559096,0.0000477273,0.002431288],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9732077,"threshold_uncertainty_score":0.7193279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009916029289897384,"score_gpt":0.199953541880671,"score_spread":0.1900375125907736,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}